Since the beginning of the 21 st century, robots have played an important role in both daily life and industrial production. This paper aims to evaluate the types of robot joint errors. First, the types of robot joint errors are described, and the two characteristic indexes, ∆ and ∆ , are identified. Next, robot joint errors are divided into adjustable ones and nonadjustable ones. A robot joint error type model is established using PB neural network model. The areas of adjustable joint errors and nonadjustable joint errors are defined. Finally, reasonable suggestions are given for different types of robot joint errors.Keywords: joint error of robot adjustable and nonadjustable; PB neural network
scite is a Brooklyn-based organization that helps researchers better discover and understand research articles through Smart Citations–citations that display the context of the citation and describe whether the article provides supporting or contrasting evidence. scite is used by students and researchers from around the world and is funded in part by the National Science Foundation and the National Institute on Drug Abuse of the National Institutes of Health.